Estimated mortality due to seasonal influenza in southeast of Iran, 2006/2007 to 2011/2012 influenza seasons

Abstract Background Global estimates showed an estimate of up to 650,000 seasonal influenza‐associated respiratory deaths annually. However, the mortality rate of seasonal influenza is unknown for most countries in the WHO Eastern Mediterranean Region, including Iran. We aimed to estimate the excess mortality attributable to seasonal influenza in Kerman province, southeast Iran for the influenza seasons 2006/2007–2011/2012. Methods We applied a Serfling model to the weekly total pneumonia and influenza (PI) mortality rate during winter to define the epidemic periods and to the weekly age‐specific PI, respiratory, circulatory, and all‐cause deaths during non‐epidemic periods to estimate baseline mortality. The excess mortality was calculated as the difference between observed and predicted mortality. Country estimates were obtained by multiplying the estimated annual excess death rates by the populations of Iran. Results We estimated an annual average excess of 40 PI, 100 respiratory, 94 circulatory, and 306 all‐cause deaths attributable to seasonal influenza in Kerman; corresponding to annual rates of 1.4 (95% confidence interval [CI] 1.1–1.8) PI, 3.6 (95% CI 2.6–4.8) respiratory, 3.4 (95% CI 2.1–5.2) circulatory, and 11.0 (95% CI 7.3–15.6) all‐cause deaths per 100,000 population. Adults ≥75 years accounted for 56% and 53% of all excess respiratory and circulatory deaths, respectively. At country level, we would expect an annual of 1119 PI to 8792 all‐cause deaths attributable to seasonal influenza. Conclusions Our findings help to define the mortality burden of seasonal influenza, most of which affects adults aged ≥75 years. This study supports influenza prevention and vaccination programs in older adults.


| INTRODUCTION
Influenza is an acute viral respiratory infection that causes substantial mortality and morbidity every year. 1 A recent global study estimated that an annual total of 290,000 to 650,000 respiratory deaths are attributable to seasonal influenza. 2 However, these estimates are lacking in many developing countries.
Influenza infections are not routinely confirmed virologically; thus, they are infrequently recorded on death certificates. 3 Moreover, virological testing might have been completed later in the course of illness, when complications from an influenza infection might be present and the virus is no longer detectable. 4 Therefore, quantifying the seasonal burden of influenza is usually done by statistical modeling approaches. 5 There are many types of time series regression models that have been used to estimate influenza-associated excess mortality. [5][6][7] Most require robust and reliable influenza virus surveillance data. 6 Among them, the Serfling regression model 8 requires the least amount of data, a minimum of 5 years with or without surveillance data. 6 Therefore, it might be considered the best choice to estimate the influenza burden in data scarce situations.
The mortality attributed to seasonal influenza has been studied in several countries of WHO regions. For example, some of the countries in the African (South Africa 9 ), Americas (Argentina 10

| Study location
This study was done in Kerman province, southeast Iran. It is geographically the largest and demographically the ninth most populous of Iran's 31 provinces with a population of 3.16 million, of which 2.2% were aged ≥75 years 14 (Text S1).

| Mortality and population data
Individual mortality records for the period of March 21, 2006, to March 19, 2013 (corresponded to seven Iranian calendar years), were obtained from the death registry office at Ministry of Health and Medical Education (MOHME) of Iran. Text S1 included a brief information about the death certificate and death registry process in Iran. Each record included information on the date of birth and death, age (in years), and ICD-10 code. Deaths due to stillbirth and those with unknown birthdate were removed. Data were aggregated into the weekly number of underlying pneumonia and influenza (PI; ICD-10 codes J10-J18), respiratory (ICD-10 codes J00-J99), circulatory (ICD-10 codes I00-I99), and all-cause (ICD-10 codes A00-U99) deaths and stratified by three age groups (≤64, 65-74, and ≥75 years).
The age-specific and total population estimates were obtained from the Statistical Center of Iran 14 for censuses in 2006, 2011, and 2016. Weekly population estimates were interpolated by a linear regression model and merged with weekly mortality data.

| Definition of influenza season
As Iran used the northern hemisphere formulation for seasonal influenza vaccine, 15 the weeks used to define influenza seasons were July

| Definition of influenza epidemic periods
As we did not have robust viral surveillance data, we used PI death rates in winter as a proxy for influenza activity. 7,8 We fitted Serfling linear regression model on observed weekly total PI death rates after excluding summer Weeks 20-40 7 ( Figure 1).
The model included linear time trend variable and trigonometric functions to adjust for seasonal fluctuations in data: where y t is the weekly total PI death rates per 100,000 population in week t, t is the week number, α is the intercept, β 1 is the coefficient for time trend, β 2 to β 5 are coefficients for annual and semi-annual seasonal fluctuations in data, and ε t is the normally distributed error terms.
Epidemic weeks were defined as any week during winter season where the observed PI death rate exceeded the one-sided upper 95% confidence interval (CI) of the baseline prediction model. 7,8 The start of each epidemic period was defined either by observing ≥2 consecutive epidemic weeks and/or one epidemic week followed by one nonepidemic week followed by one another epidemic week, to be more conservative; and the epidemic period ended with ≥3 consecutive non-epidemic weeks. 7 Therefore, in each season ≥1 epidemic periods were possible.

| Estimation of influenza-associated deaths
We applied Serfling model to the interrupted time series of age and death cause groups, after excluding weeks inside the epidemic periods, to predict the weekly baseline mortality rates and 95% CIs in the absence of influenza activity 7 ( Figure 1). The annual excess mean number and rate were calculated across all influenza seasons.
Due to the excess zeros in the age-specific PI mortality data, only the total influenza-associated PI mortality were calculated.
As Kerman is the province most representative of Iran's climate 19 and has nearly the same proportion of people aged ≥75 years as the whole country (2.2% vs. 2.5%), 14 to have a general overview of the influenza-associated deaths for the country, we applied the mean of age-specific and total annual excess death rates estimated for Kerman province across the six seasons to the age-specific and total population of Iran at the time of 2016 census. 14

| Over-dispersion assessment
To assess the impact of over-dispersion in our data, we applied the Serfling approach in the negative binomial regression model, 20 both to define the influenza epidemic periods and estimate the excess deaths associated with influenza. Our Serfling negative binomial model was þ β 3 cos 2πt 52:17 þ β 4 sin 4πt 52:17 where y t is the weekly number of deaths in each age group and death cause category, α is the offset term (log of weekly age-specific population), and δ t is the over-dispersion parameter. Other terms were similar to the Serfling linear model.
All analyses were done with Stata (Version 13). 3) for all-cause deaths. In most years, adults ≥75 years represented more than 50% of deaths due to underlying PI, respiratory, and circulatory diseases (Table S1).

| Estimates of influenza-associated mortality by influenza season
The excess mortality associated with influenza varied by influenza  Our estimated PI excess death rate per 100,000 population is comparable with the estimates of 2.2 in Thailand, 11 1.4 in Brazil, 21 and 2.9 in Singapore 22 but is lower than 6.0 in Argentina, 10  (95% CI 0.7-1.0), lower than our estimate using registered PI deaths.
The impact of influenza on the excess all-cause mortality rate was similar to other studies done in China, 26 Canada, 27 and Hong Kong. 23 Similar to China 26 and Hong Kong, 23 we observed 2.8% of all observed deaths were associated with influenza.
Our findings on the respiratory deaths attributed to influenza are consistent with estimates of China 26 and Thailand 11 but slightly lower than the United States. 24 Additionally, we estimated a higher rate of influenza-associated respiratory deaths, both in total and by age groups, than the global study which provided an estimate for Iran's influenza-associated respiratory deaths through extrapolation simulation methods 2 ; this might be due to the use of WHO global health estimates of respiratory infection mortality rates to categorize countries in analytic divisions instead of the country-specific seasonal influenza case fatality ratio. Moreover, a constant seasonal influenza attack rate between countries was assumed. However, the ranges for the simulated estimates were broader. We estimated an annual excess rate of 0.9 (95% CI 0. Studies suggest that there is no gold standard modeling approach to estimate influenza-associated deaths. 6,35 As our dependent variable was the count of deaths in a given week and might be over-dispersed, we tried to assess the impact of over-dispersion by introducing the Serfling approach in a negative binomial model. Although we have found a strong association between the results of Serfling linear and negative binomial models and a similar baseline predicted mortality in the absence of influenza activity, future studies should be conducted to confirm our results with and without inclusion of influenza viral surveillance parameters in statistical modeling approaches.
There are some considerations in interpreting of our findings.
Although the completeness of the death registry system in Kerman is the highest in Iran, 36  Iran was previously estimated at 2 per 1,000,000 persons. 38

| CONCLUSION
In Kerman province, we found a mortality burden of seasonal influenza similar to that of other studies and a disproportionate burden among adults aged ≥75 years. Our findings highlight the potential value of comprehensive influenza prevention strategies, including vaccination programs in older adults, campaigns for awareness of influenza vaccination, and simple prevention strategies (i.e., hand washing and respiratory hygiene).

ACKNOWLEDGMENTS
We would like to express our appreciation to all those in the Depart- supervision; writing-review and editing.

CONFLICT OF INTEREST
No conflict of interest declared.

ETHICS APPROVAL
The ethics committee of the Kerman University of Medical Sciences approved our study (code IR.KMU.REC.1395.423).

PATIENT CONSENT TO PARTICIPATE
Because we used aggregated data and there was no personal information, no informed consent was required.

DISCLAIMER
The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention.

PEER REVIEW
The peer review history for this article is available at https://publons. com/publon/10.1111/irv.13061.

DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from Ministry of Health and Medical Education of Iran but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available.